There is some descriptive evidence demonstrating that there are gender differences in schizophrenia regarding age of onset, premorbid history, family history, psychopathology, and course. However, much of the literature on schizophrenia assumes that the illness is similar in men and women. The validity of the effect of gender on schizophrenia has important consequences for understaanding the nature of the illness. That is, if there are significant differences in the family history, expression, and course of the illness, perhaps men and women express different subtypes of schizophrenia. This has been proposed by some who argue that schizophrenic men may be at higher risk for an amotivational (negative) syndrome than schizophrenic women. The proposed study will test this hypothesis by examining four of the validity criteria of Robins and Guze (1970): the clinical description, family history, and course of the disorder, and the specificity of the gender effects on schizophrenia compared to major affective disorder. Hypotheses will be tested using the data from the well-known retrospective cohort studies, the Iowa 500 and Non-500 studies. Subjects have been rediagnosed by expert diagnosticians using DSM-III criteria, which will allow for stringent tests of the gender hypotheses. This data set provides a sample size with the power to test for the validity of gender effects, has a long observational period, and has important variables necessary to test for gender effects such as age of onset, premorbid history, family history, symptomatology, and social functioning, and includes psychiatric and normal controls. Finally, this data set allows for the opportunity to test models that begin to explain the effect of gender on schizophrenia, which have important implications for understanding the nature of the illness. The hypotheses will be tested using powerful data analytic techniques that have been recently developed for use with the type of data available for this proposal. They include survival analysis to estimate age of onset distributions and family morbidity risk, maximum likelihood procedures to test competing models of familial transmission, latent class analysis to test for gender differences in psychopathology, and log linear analyses to test models to explain the effect of gender on schizophrenia. This study will provide a valuable contribution to understanding the heterogeneity of schizophrenia, has methodological consequences for estimating the morbidity risk, and costs considerably low given the benefits.